tsfresh.scripts package

Submodules

tsfresh.scripts.measure_execution_time module

class tsfresh.scripts.measure_execution_time.CombinerTask(*args, **kwargs)

Bases: Task

Collect all tasks into a single result.csv file

complete()

If the task has any outputs, return True if all outputs exist. Otherwise, return False.

However, you may freely override this method with custom logic.

output()

The output that this Task produces.

The output of the Task determines if the Task needs to be run–the task is considered finished iff the outputs all exist. Subclasses should override this method to return a single Target or a list of Target instances.

Implementation note

If running multiple workers, the output must be a resource that is accessible by all workers, such as a DFS or database. Otherwise, workers might compute the same output since they don’t see the work done by other workers.

See Task.output

requires()

The Tasks that this Task depends on.

A Task will only run if all of the Tasks that it requires are completed. If your Task does not require any other Tasks, then you don’t need to override this method. Otherwise, a subclass can override this method to return a single Task, a list of Task instances, or a dict whose values are Task instances.

See Task.requires

run()

The task run method, to be overridden in a subclass.

See Task.run

class tsfresh.scripts.measure_execution_time.DataCreationTask(*args, **kwargs)

Bases: Task

Create random data for testing

num_ids = <luigi.parameter.IntParameter object>

output()

The output that this Task produces.

The output of the Task determines if the Task needs to be run–the task is considered finished iff the outputs all exist. Subclasses should override this method to return a single Target or a list of Target instances.

Implementation note

If running multiple workers, the output must be a resource that is accessible by all workers, such as a DFS or database. Otherwise, workers might compute the same output since they don’t see the work done by other workers.

See Task.output

random_seed = <luigi.parameter.IntParameter object>

run()

The task run method, to be overridden in a subclass.

See Task.run

time_series_length = <luigi.parameter.IntParameter object>

class tsfresh.scripts.measure_execution_time.FullTimingTask(*args, **kwargs)

Bases: Task

Run tsfresh with all calculators for comparison

n_jobs = <luigi.parameter.IntParameter object>

num_ids = <luigi.parameter.IntParameter object>

output()

The output that this Task produces.

The output of the Task determines if the Task needs to be run–the task is considered finished iff the outputs all exist. Subclasses should override this method to return a single Target or a list of Target instances.

Implementation note

If running multiple workers, the output must be a resource that is accessible by all workers, such as a DFS or database. Otherwise, workers might compute the same output since they don’t see the work done by other workers.

See Task.output

random_seed = <luigi.parameter.IntParameter object>

requires()

The Tasks that this Task depends on.

A Task will only run if all of the Tasks that it requires are completed. If your Task does not require any other Tasks, then you don’t need to override this method. Otherwise, a subclass can override this method to return a single Task, a list of Task instances, or a dict whose values are Task instances.

See Task.requires

run()

The task run method, to be overridden in a subclass.

See Task.run

time_series_length = <luigi.parameter.IntParameter object>

class tsfresh.scripts.measure_execution_time.TimingTask(*args, **kwargs)

Bases: Task

Run tsfresh with the given parameters

feature_parameter = <luigi.parameter.DictParameter object>

n_jobs = <luigi.parameter.IntParameter object>

num_ids = <luigi.parameter.IntParameter object>

output()

The output that this Task produces.

The output of the Task determines if the Task needs to be run–the task is considered finished iff the outputs all exist. Subclasses should override this method to return a single Target or a list of Target instances.

Implementation note

If running multiple workers, the output must be a resource that is accessible by all workers, such as a DFS or database. Otherwise, workers might compute the same output since they don’t see the work done by other workers.

See Task.output

random_seed = <luigi.parameter.IntParameter object>

requires()

The Tasks that this Task depends on.

A Task will only run if all of the Tasks that it requires are completed. If your Task does not require any other Tasks, then you don’t need to override this method. Otherwise, a subclass can override this method to return a single Task, a list of Task instances, or a dict whose values are Task instances.

See Task.requires

run()

The task run method, to be overridden in a subclass.

See Task.run

time_series_length = <luigi.parameter.IntParameter object>

try_number = <luigi.parameter.IntParameter object>

tsfresh.scripts.run_tsfresh module

This script can be run with:

python run_tsfresh.py path_to_your_csv.csv

A corresponding csv containing time series features will be saved as features_path_to_your_csv.csv

There are a few limitations though

• Currently this only samples to first 50 values.

• Your csv must be space delimited.

• Output is saved as path_to_your_csv.features.csv

tsfresh.scripts.run_tsfresh.main(console_args=None)

tsfresh.scripts.test_timing module

tsfresh.scripts.test_timing.measure_temporal_complexity()

tsfresh.scripts.test_timing.plot_results()

tsfresh.scripts.test_timing.simulate_with_length(length, df)

Module contents